Hi Community,

Are you ready to transform your healthcare organization with the power of Artificial Intelligence? Join us for an enlightening webinar that will equip you with the knowledge and tools to harness AI effectively in your practice.

🌐 Are you and your data AI ready? 🌐

📅 Tuesday, 15th October, 1 pm ICT | 2 pm SGT| 4 pm AEST // 8 am CEST |  2 am EDT 

🗣 Presenter: @Kathleen Aller, Global Head of Healthcare Market Strategy, InterSystems

Hi Community,

Play the new video on InterSystems Developers YouTube:

⏯ Deployment Considerations for Your AI Solution @ Global Summit 2024

Hi, Community!

Want to dive deeper into the concepts of vector searches and embeddings? Learn from an InterSystems expert:

What Are Embeddings?

Hi, Community!

What components and libraries can you add to your retrieval-augmented generation (RAG) applications? Find out in this video:

Identifying Useful Components for Your Generative AI Application

Hi Community,

Play the new video on InterSystems Developers YouTube:

⏯ InterSystems IRIS Vector Search and the Python Ecosystem @ Global Summit 2024

In today's data landscape, businesses encounter a number of different challenges. One of them is to do analytics on top of unified and harmonized data layer available to all the consumers. A layer that can deliver the same answers to the same questions irrelative to the dialect or tool being used. InterSystems IRIS Data Platform answers that with and add-on of Adaptive Analytics that can deliver this unified semantic layer. There are a lot of articles in DevCommunity about using it via BI tools.

Hi, Community!

Curious how a retrieval-augmented generation (RAG) application works? Take a look at this demonstration:

Exploring a Basic RAG Application

Hi, Community!

Ready to create a retrieval-augmented generation (RAG) architecture for your next GenAI application? See how to get started:

Setting Up Your Generative AI Development Environment

Hey Community!

We’re thrilled to invite you to an exciting LinkedIn Live session dedicated to the most common myths and misconceptions surrounding AI!

🌐 Debunking AI Myths with Expert Insights 🌐

📅 Thursday, September 5th, 10 am EDT | 4 pm CEST

🗣 Presenters:

• @John Paladino, Head of Client Services, InterSystems
• Tobias Zwingmann, AI Expert

Hi, Community!

Are you ready to start developing a generative AI application? Learn how you can make it as effective as possible:

Planning Your Generative AI Project

Hi, Community!

Are you building generative AI applications? See how a retrieval-augmented generation (RAG) architecture can help:

Exploring the Benefits of RAG

Hi, Community!

How can you get your data ready for generative AI applications? Get some key tips from an InterSystems expert:

Preparing Your Data for Use with Generative AI

Hi, Community!

Are you using generative AI tools for development? Let InterSystems principles be your guiding star! 🌟 Learn about the company's approach:

Using Generative AI Responsibly

I received some really excellent feedback from a community member on my submission to the Python 2024 contest. I hope its okay if I repost it here:

you build a container more than 5 times the size of pure IRIS

and this takes time

container start is also slow but completes

backend is accessible as described

a production is hanging around

frontend reacts

I fail to understand what is intended to show

the explanation is meant for experts other than me

The submission is here: https://openexchange.intersystems.

In the previous article we presented the d[IA]gnosis application developed to support the coding of diagnoses in ICD-10. In this article we will see how InterSystems IRIS for Health provides us with the necessary tools for the generation of vectors from the ICD-10 code list using a pre-trained language model, its storage and the subsequent search for similarities on all these generated vectors.

Hi, Community!

Need to learn how to write better prompts for GenAI? This video from Learning Services introduces six key strategies:

▶ Optimizing Your Prompts for Generative AI

The invention and popularization of Large Language Models (such as OpenAI's GPT-4) has launched a wave of innovative solutions that can leverage large volumes of unstructured data that was impractical or even impossible to process manually until recently. Such applications may include data retrieval (see Don Woodlock's ML301 course for a great intro to Retrieval Augmented Generation), sentiment analysis, and even fully-autonomous AI agents, just to name a few!

Hi, Community!

Do you think Generative AI can make your life easier? See some potential use cases for GenAI in the latest video from Learning Services:

▶ Generative AI in Use

Hi Community!

How can you create a balanced approach to using Generative AI? Get help from InterSystems experts in the latest video from Learning Services:

⚖ Weighing the Benefits and Risks of Generative AI

Hi Community,

Watch this video to learn about the PainChek artificial intelligence technology, which assesses patient pain at the hospital bedside, leverages InterSystems IRIS interoperability to connect to third-party electronic medical record systems:

⏯ Using Artificial Intelligence / Machine Learning for Pain Assessment in a Clinical Environment @ Global Summit 2023

Hi Community!

Need an introduction to Generative AI? Learning Services is excited to announce the first video in a new series about GenAI basics:

🧐 What Is Generative AI?

Hey Community!

We're happy to share our newest learning path dedicated to the essentials of GenAI, accessible on the Learning Portal via your SSO:

🤖 Getting Started with Generative AI🤖

Here is what you can expect:

Collision Theory Confirmed

Looking to get started with generative AI? Try two brand-new learning paths. In Getting Started with Generative AI (2h 45m), learn the basics of interacting with GenAI. Then, try Developing Generative AI Applications (2h) to start developing your own GenAI application. Plus, earn badges for completing each path!

We have a yummy dataset with recipes written by multiple Reddit users, however most of the information is free text as the title or description of a post. Let's find out how we can very easily load the dataset, extract some features and analyze it using features from OpenAI large language model within Embedded Python and the Langchain framework.

Loading the dataset

First things first, we need to load the dataset or can we just connect to it?

Hi All,
We invite you to join our next Meetup in Boston on June 25 5:30-7:30 pm.
>> RSVP here <<

Continuing with the series of articles on voice file management, we are going to see how we can convert text into audio and receive the file with the chosen voice.
We will also explore how a service from OpenAI can help us analyze a text and determine the mood expressed in it.
Let's analyze how you can create your own voice file and how it can “read” your feelings.

ChatIRIS Health Coach, a GPT-4 based agent that leverages the Health Belief Model as a psychological framework to craft empathetic replies. This article elaborates on the backend architecture and its components, focusing on how InterSystems IRIS supports the system's functionality.

ChatIRIS Health Coach, a GPT-4 based agent that leverages the Health Belief Model (Hochbaum, Rosenstock, & Kegels, 1952) as a psychological framework to craft empathetic replies.

TL;DR

This article introduces using the langchain framework supported by IRIS for implementing a Q&A chatbot, focusing on Retrieval Augmented Generation (RAG). It explores how IRIS Vector Search within langchain-iris facilitates storage, retrieval, and semantic search of data, enabling precise and up-to-date responses to user queries. Through seamless integration and processes like indexing and retrieval/generation, RAG applications powered by IRIS enable the capabilities of GenAI systems for InterSystems developers.